| 書目名稱 | Fluctuation-Induced Network Control and Learning | | 副標(biāo)題 | Applying the Yuragi | | 編輯 | Masayuki Murata,Kenji Leibnitz | | 視頻video | http://file.papertrans.cn/345/344520/344520.mp4 | | 概述 | Provides an interdisciplinary computational approach applying bio- and neuroscience to communication network control.Proposes noise-driven machine-learning methods utilizing the latest findings in hum | | 圖書封面 |  | | 描述 | From theory to application, this book presents research on biologically?and brain-inspired networking?and machine learning?based on?Yuragi, which is the Japanese term describing the noise or fluctuations that?are inherently used to control the dynamics of a system. The?Yuragi?mechanism can be found in various biological contexts, such as in gene expression dynamics, molecular motors in muscles, or the visual recognition process in the brain. Unlike conventional network protocols that are usually designed to operate under controlled conditions with a predefined set of rules, the probabilistic behavior of Yuragi-based control permits the system to adapt to unknown situations in a distributed and self-organized manner leading to a higher scalability and robustness..The book consists of two parts. Part 1 provides in four chapters an introduction to the biological background of the Yuragi concept as well as how these are applied to networking problems. Part 2 provides additional contributions that extend the original Yuragi concept to a Bayesian attractor model from human perceptual decision making.?In the six chapters?of the second part, applications to various fields in information ne | | 出版日期 | Book 2021 | | 關(guān)鍵詞 | Bio-inspired networking; brain-inspired networking; uncertainty; dynamic environment; decision-making; se | | 版次 | 1 | | doi | https://doi.org/10.1007/978-981-33-4976-6 | | isbn_softcover | 978-981-33-4978-0 | | isbn_ebook | 978-981-33-4976-6 | | copyright | Springer Nature Singapore Pte Ltd. 2021 |
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